Hourly forecasting of the photovoltaic electricity at any latitude using a network of artificial neural networks

N Matera, D Mazzeo, C Baglivo… - … Energy Technologies and …, 2023 - Elsevier
Nowadays, special attention is paid to the importance of using photovoltaic (PV) systems to
tackle the problem of climate change and the energy crisis. Artificial intelligence is currently …

A water cycle approach for maximum power point tracking through an interleaved boost converter

K Krishnaram… - … Power Components and …, 2023 - Taylor & Francis
In this work, an Interleaved Boost Converter (IBC) is developed for Sun Powered E-vehicles
(SPEVs) to reduce input/output filters, improve dynamic characteristics, and minimize device …

Detection and classification of photovoltaic module defects based on artificial intelligence

WM Shaban - Neural Computing and Applications, 2024 - Springer
Photovoltaic (PV) system performance and reliability can be improved through the detection
of defects in PV modules and the evaluation of their effects on system operation. In this …

Assessing the performance of a monocrystalline solar panel under different tropical climatic conditions in Cameroon using artificial neural network

CO Dongmo, NA Arreyndip, E Tendong… - Journal of Renewable …, 2024 - pubs.aip.org
To implement the European Union (EU)-Africa Green Energy Initiative in Cameroon to boost
the renewable energy sector, we model the performance of a 500 W monocrystalline solar …

A hybrid machine-learning model for solar irradiance forecasting

AM Almarzooqi, M Maalouf, THM El-Fouly… - Clean …, 2024 - academic.oup.com
Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-
connected solar photovoltaic (PV) power plants. These plants face operational challenges …